This is a proposal to establish a new research training program in the genetic epidemiology and statistical analysis of psychiatric and other complex diseases. The field of psychiatric genetics is changing rapidly, and successful investigators must be competent in a broad array of techniques, must be able to speak the languages of fields outside their own, and must be able to collaborate effectively with scientists in other fields. The program will train postdoctoral (M.D. and Ph.D.) and predoctoral Fellows. Training will have both a didactic and a research component. The didactic component will be further broken down into an academic program and a series of practical laboratory rotations. The academic program includes a series of academic courses in human genetics, epidemiology, statistical genetics, computer simulations, research communication skills, and responsible conduct of research. The laboratory rotations will take place in a number of laboratories at Columbia University, where a rich and broad variety of genetic studies are being carried out. In the research component each Fellow will work closely with a Preceptor on an independent research project of the Fellow?s choosing; the Fellow will prepare a clearly written research proposal, carry out the proposal, prepare an oral description of the study and its results, and prepare a publishable manuscript based on the completed study. At the end of training, Fellows should understand: the biological underpinnings of genetic influences on disease risk; how to formulate testable hypotheses in human genetics and design studies to test those hypotheses; the critical importance of phenotype definition; the factors that go into selecting appropriate samples; issues of responsible conduct of research and Good Clinical Practice; the mathematical underpinnings of genetic analysis, including familial aggregation studies, twin studies, and segregation, linkage, and association analysis; laboratory techniques such as genotyping and sequencing, extracting DNA from blood, PCR, etc.; proper data management of genetic and clinical data through the use of a data base management system; how to use current genetic analysis programs, to interpret the results, and to test and evaluate new methods of genetic analysis as they become available; and microarray technology and other current molecular-biological techniques.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Institutional National Research Service Award (T32)
Project #
1T32MH065213-01
Application #
6453928
Study Section
Special Emphasis Panel (ZMH1-BRB-P (01))
Program Officer
Wynne, Debra K
Project Start
2002-07-15
Project End
2007-06-30
Budget Start
2002-07-15
Budget End
2003-06-30
Support Year
1
Fiscal Year
2002
Total Cost
$159,584
Indirect Cost
Name
Columbia University (N.Y.)
Department
Psychiatry
Type
Schools of Medicine
DUNS #
167204994
City
New York
State
NY
Country
United States
Zip Code
10032
Subaran, Ryan L; Odgerel, Zagaa; Swaminathan, Rajeswari et al. (2016) Novel variants in ZNF34 and other brain-expressed transcription factors are shared among early-onset MDD relatives. Am J Med Genet B Neuropsychiatr Genet 171B:333-41
Corso, Barbara; Greenberg, David A (2014) Using linkage analysis to detect gene-gene interaction by stratifying family data on known disease, or disease-associated, alleles. PLoS One 9:e93398
Lipner, E M; Tomer, Y; Noble, J A et al. (2013) HLA class I and II alleles are associated with microvascular complications of type 1 diabetes. Hum Immunol 74:538-44
Hodge, Susan E; Subaran, Ryan L; Weissman, Myrna M et al. (2012) Designing case-control studies: decisions about the controls. Am J Psychiatry 169:785-9
Subaran, Ryan L; Talati, Ardesheer; Hamilton, Steven P et al. (2012) A survey of putative anxiety-associated genes in panic disorder patients with and without bladder symptoms. Psychiatr Genet 22:271-8
Stewart, William C L; Subaran, Ryan L (2012) Obtaining accurate p values from a dense SNP linkage scan. Hum Hered 74:12-6
Stewart, William C L; Drill, Esther N; Greenberg, David A (2011) Finding disease genes: a fast and flexible approach for analyzing high-throughput data. Eur J Hum Genet 19:1090-4
Greenberg, David A; Subaran, Ryan (2011) Blinders, phenotype, and fashionable genetic analysis: a critical examination of the current state of epilepsy genetic studies. Epilepsia 52:1-9
Madsen, Ann M; Hodge, Susan E; Ottman, Ruth (2011) Causal models for investigating complex disease: I. A primer. Hum Hered 72:54-62
Fung, Eva Lai-wah; Ho, Yuan Yuan; Hui, Joannie et al. (2011) First report of GLUT1 deficiency syndrome in Chinese patients with novel and hot spot mutations in SLC2A1 gene. Brain Dev 33:170-3

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